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Method for predicting stock trends by applying deep learning technology

A trend prediction and deep learning technology, applied in the field of machine learning, can solve problems such as limited expression ability of complex functions

Inactive Publication Date: 2017-06-13
GUANGDONG UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The present invention aims to overcome the deficiencies of the existing stock trend forecasting methods, including the limited ability of the existing methods to express complex functions, and the need for a large number of professionals to design appropriate index systems, etc.

Method used

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  • Method for predicting stock trends by applying deep learning technology
  • Method for predicting stock trends by applying deep learning technology

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0039]An example is given below, using the market historical transaction data of A shares in Shenzhen, China as the implementation data set. Use the FQuantToolBox toolbox to collect all stocks of China’s Shenzhen A-shares from the date of listing (with January 1, 2006 as the boundary, if the stock’s listing date is before that, start collecting data from that day) to November 30, 2016 Daily transaction information, including opening price, closing price, highest price, lowest price, transaction volume, transaction amount, all price information is the ex-right price information provided by the data provider. There are a total of 1906 stocks in the data set, and a total of 213120 data records.

[0040] (1). Data normalization

[0041] According to the content of the invention (1).B step, for example, for the stock 002003, from January 1, 2006 to November 30, 2016, there are a total of 2527 daily transaction data records. For the opening price field, it has been ex-righted The ...

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Abstract

Existing stock forecasting methods can only rely on expert knowledge and the screening and refining of market data and information. It is difficult to directly model from market data to operating laws, or they are mostly based on various market indicators. These indicators include: Specific calculation formulas can reflect some characteristics of the market, but they have transformed the most original transaction data, resulting in information loss to some extent. The present invention proposes a stock trend forecasting method using deep learning technology, using deep learning technology to establish a stock trend model, using historical daily transaction data as training data to train the model, and using transaction data for a period of time before the current trading day to predict a period of time after the current trading day trend is predicted. The purpose of the present invention is to discover potential profit opportunities in the current market from the historical transaction data of the market through a deep learning method, and guide the investment behavior of institutional investors and individual investors.

Description

technical field [0001] The technical field of the present invention is the field of machine learning, specifically a stock trend prediction method using deep learning technology. Background technique [0002] The securities market has its own operating laws. Although it will be affected by various uncontrollable external factors, within a certain period of time, this operating law still plays a role and affects the price trend of securities. However, due to the large amount of various data and information in the securities market, companies in the industry also need a dedicated team of analysts to analyze stocks. The ability to conduct comprehensive and efficient analysis. However, the mastery of the operating laws of the securities market is helpful to make profits in the market, so it has attracted the attention of institutional investors and individual investors. Literature "Ved Prakash Upadhyay, Subhash Panwar, Ramchander Merugu, and Ravindra Panchariya. 2016. Forecast...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q40/04
CPCG06Q10/04G06Q40/04
Inventor 张钢王玉乐陈广强
Owner GUANGDONG UNIV OF TECH
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